Triple
T7985391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yet Another Resource Negotiator |
E185671
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | component of Apache Hadoop |
C11253
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: component of Apache Hadoop Context triple: [Yet Another Resource Negotiator, instanceOf, component of Apache Hadoop]
-
A.
big data framework
chosen
A big data framework is a software platform that enables the distributed storage, processing, and analysis of large-scale, complex datasets across clusters of machines.
-
B.
Java platform component
A Java platform component is a modular part of the Java ecosystem—such as the JVM, core libraries, or development tools—that provides specific functionality enabling Java applications to run and be developed consistently across environments.
-
C.
component of the Cybersecurity and Infrastructure Security Agency
A component of the Cybersecurity and Infrastructure Security Agency is an organizational unit or program within CISA that carries out specific cybersecurity, infrastructure protection, emergency communications, or risk management functions in support of the agency’s mission.
-
D.
component of the Centers for Medicare & Medicaid Services
A component of the Centers for Medicare & Medicaid Services is an organizational unit within CMS responsible for specific functions such as policy development, program administration, oversight, or support related to Medicare, Medicaid, and other health coverage programs.
-
E.
data engineering tool
A data engineering tool is a software solution that enables the collection, transformation, orchestration, and management of data pipelines to ensure reliable, scalable, and efficient data processing.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
Created at: March 30, 2026, 5:15 p.m.